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An integrated energy-efficient train operation approach based on the space-time-speed network methodology

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  • Wang, Xuekai
  • Tang, Tao
  • Su, Shuai
  • Yin, Jiateng
  • Gao, Ziyou
  • Lv, Nan

Abstract

Reduction on the traction energy and increasing of the reused regenerative energy are two main ways for saving energy in metro systems, which are related to the driving strategy as well as the train timetable. To minimize the systematic energy, this paper proposes an integrated energy-efficient train operation method in which the driving strategy and the train timetable are jointly optimized. Firstly, the models of calculating the traction energy and the reuse of the regenerate energy are introduced with the constraints of the train operation. Then, the systematical optimization model is formulated by taking the net energy (i.e., the difference between the traction energy and the reused regenerate energy) as the objective function. Based on the Space–-Time-Speed network methodology, the optimization model is transformed into a discrete decision problem. Next, two algorithms are used to solve the problem. The dynamic programming algorithm is used to obtain the global optimal solution, and the discrete differential dynamic programming algorithm is applied to get the approximate optimal solution to reduce the computing time. Finally, two numeral examples are conducted to illustrate the effectiveness of the proposed method on energy saving. The method can reduce the net energy consumption by up to 25.0% compared to the result without optimization and by up to 8.7% compared to the result by using the two-stage method.

Suggested Citation

  • Wang, Xuekai & Tang, Tao & Su, Shuai & Yin, Jiateng & Gao, Ziyou & Lv, Nan, 2021. "An integrated energy-efficient train operation approach based on the space-time-speed network methodology," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 150(C).
  • Handle: RePEc:eee:transe:v:150:y:2021:i:c:s1366554521000971
    DOI: 10.1016/j.tre.2021.102323
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    References listed on IDEAS

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    1. Xie, J. & Wong, S.C. & Zhan, S. & Lo, S.M. & Chen, Anthony, 2020. "Train schedule optimization based on schedule-based stochastic passenger assignment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    2. Wang, Pengling & Goverde, Rob M.P., 2019. "Multi-train trajectory optimization for energy-efficient timetabling," European Journal of Operational Research, Elsevier, vol. 272(2), pages 621-635.
    3. Wang, Pengling & Goverde, Rob M.P., 2017. "Multi-train trajectory optimization for energy efficiency and delay recovery on single-track railway lines," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 340-361.
    4. Canca, David & Zarzo, Alejandro, 2017. "Design of energy-Efficient timetables in two-way railway rapid transit lines," Transportation Research Part B: Methodological, Elsevier, vol. 102(C), pages 142-161.
    5. Xiaowen Wang & Zhuang Xiao & Mo Chen & Pengfei Sun & Qingyuan Wang & Xiaoyun Feng, 2020. "Energy-Efficient Speed Profile Optimization and Sliding Mode Speed Tracking for Metros," Energies, MDPI, vol. 13(22), pages 1-29, November.
    6. Lai, Qingying & Liu, Jun & Haghani, Ali & Meng, Lingyun & Wang, Yihui, 2020. "Energy-efficient speed profile optimization for medium-speed maglev trains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    7. Feng, Zhong-kai & Niu, Wen-jing & Cheng, Chun-tian & Liao, Sheng-li, 2017. "Hydropower system operation optimization by discrete differential dynamic programming based on orthogonal experiment design," Energy, Elsevier, vol. 126(C), pages 720-732.
    8. Albrecht, Amie & Howlett, Phil & Pudney, Peter & Vu, Xuan & Zhou, Peng, 2016. "The key principles of optimal train control—Part 2: Existence of an optimal strategy, the local energy minimization principle, uniqueness, computational techniques," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 509-538.
    9. Shuai Su & Tao Tang & Yihui Wang, 2016. "Evaluation of Strategies to Reducing Traction Energy Consumption of Metro Systems Using an Optimal Train Control Simulation Model," Energies, MDPI, vol. 9(2), pages 1-19, February.
    10. Cadarso, Luis & Marín, Ángel & Maróti, Gábor, 2013. "Recovery of disruptions in rapid transit networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 53(C), pages 15-33.
    11. Ning, Jingjie & Zhou, Yonghua & Long, Fengchu & Tao, Xin, 2018. "A synergistic energy-efficient planning approach for urban rail transit operations," Energy, Elsevier, vol. 151(C), pages 854-863.
    12. Albrecht, Amie & Howlett, Phil & Pudney, Peter & Vu, Xuan & Zhou, Peng, 2016. "The key principles of optimal train control—Part 1: Formulation of the model, strategies of optimal type, evolutionary lines, location of optimal switching points," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 482-508.
    13. Wang, Yihui & Tang, Tao & Ning, Bin & Meng, Lingyun, 2017. "Integrated optimization of regular train schedule and train circulation plan for urban rail transit lines," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 105(C), pages 83-104.
    14. Phil Howlett, 2000. "The Optimal Control of a Train," Annals of Operations Research, Springer, vol. 98(1), pages 65-87, December.
    15. Zhou, Leishan & Tong, Lu (Carol) & Chen, Junhua & Tang, Jinjin & Zhou, Xuesong, 2017. "Joint optimization of high-speed train timetables and speed profiles: A unified modeling approach using space-time-speed grid networks," Transportation Research Part B: Methodological, Elsevier, vol. 97(C), pages 157-181.
    16. Yin, Jiateng & Tang, Tao & Yang, Lixing & Gao, Ziyou & Ran, Bin, 2016. "Energy-efficient metro train rescheduling with uncertain time-variant passenger demands: An approximate dynamic programming approach," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 178-210.
    17. Liu, Rongfang (Rachel) & Golovitcher, Iakov M., 2003. "Energy-efficient operation of rail vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(10), pages 917-932, December.
    18. Li, Xiang & Lo, Hong K., 2014. "An energy-efficient scheduling and speed control approach for metro rail operations," Transportation Research Part B: Methodological, Elsevier, vol. 64(C), pages 73-89.
    19. Yin, Jiateng & Yang, Lixing & Tang, Tao & Gao, Ziyou & Ran, Bin, 2017. "Dynamic passenger demand oriented metro train scheduling with energy-efficiency and waiting time minimization: Mixed-integer linear programming approaches," Transportation Research Part B: Methodological, Elsevier, vol. 97(C), pages 182-213.
    20. Yang, Xin & Chen, Anthony & Ning, Bin & Tang, Tao, 2017. "Bi-objective programming approach for solving the metro timetable optimization problem with dwell time uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 97(C), pages 22-37.
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    Cited by:

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    3. Zhou, Wenliang & Huang, Yu & Deng, Lianbo & Qin, Jin, 2023. "Collaborative optimization of energy-efficient train schedule and train circulation plan for urban rail," Energy, Elsevier, vol. 263(PA).
    4. Shi, Jungang & Yang, Jing & Yang, Lixing & Tao, Lefeng & Qiang, Shengjie & Di, Zhen & Guo, Junhua, 2023. "Safety-oriented train timetabling and stop planning with time-varying and elastic demand on overcrowded commuter metro lines," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    5. Wang, Xuekai & D’Ariano, Andrea & Su, Shuai & Tang, Tao, 2023. "Cooperative train control during the power supply shortage in metro system: A multi-agent reinforcement learning approach," Transportation Research Part B: Methodological, Elsevier, vol. 170(C), pages 244-278.

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